CO and CO2 emission ratio coefficient estimation method, device, storage medium and terminal

Abstract

The present invention discloses a method and device for estimating the ratio coefficient of CO and CO2 emissions, a storage medium and a terminal, wherein the method comprises: determining the area to be analyzed and the time to be analyzed; obtaining meteorological reanalysis data and gas data at the time to be analyzed in the area to be analyzed; obtaining the CO assimilation grid flux data set, the CO2 assimilation grid flux data set, the CO prediction regional flux and the CO2 prediction regional flux at the time to be analyzed by a preset acquisition method; obtaining the CO and CO2 emission ratio coefficient; the gas data comprises CO initial boundary field data, preset mixed gas initial boundary field data, CO ecological flux data, CO wildfire flux data, CO anthropogenic flux data, CO satellite observation data, CO2 initial boundary field data, CO2 flux data and CO2 satellite observation data. The method of the present invention can obtain the ratio coefficient of CO2 and CO with spatiotemporal characteristics in different countries, provinces, municipalities and regions around the world; and the obtained ratio coefficients of different regions are comparable.

Description

Technical Field

[0001] The present invention relates to the technical field of atmospheric chemistry, in particular to a method for 2 Emission proportionality coefficient estimation method and device, storage medium and terminal. Background Art

[0002] During the combustion and conversion of energy, CO 2 Emissions, while incomplete combustion will produce CO emissions, so CO 2 and CO are the same emission gases. 2 The relationship between the ratio of carbon dioxide emissions to CO emissions is helpful to study the level of regional energy technology development and reveal the law of anthropogenic carbon emissions, providing data support for the "dual carbon" goal. 2 With the development of remote sensing technology, it is necessary to use satellite observation data to obtain regional CO 2 and CO ratio coefficient provide conditions.

[0003] Existing observation data from ground stations are used to conduct CO 2 The main data source for the estimation of the CO ratio coefficient is ground stations, and satellite data is not used. 2 The CO ratio coefficient uses concentration data, and its artificial CO 2 The CO2 ratio coefficient is directly derived from inventory data without model optimization. The above factors make the existing CO 2 The estimation of the CO proportionality coefficient is not continuous in time and space, and the accuracy is not high. Summary of the invention

[0004] The technical problem to be solved by the present invention is that the existing CO 2 Compared with the CO proportional coefficient estimation method, the estimation time and space are not continuous and the estimation accuracy is not high.

[0005] In order to solve the above technical problems, the present invention provides a CO and CO 2 Emission proportionality factor estimation method, including:

[0006] Determine the area and time to be analyzed;

[0007] Obtain meteorological reanalysis data and gas data for the area to be analyzed at the time to be analyzed;

[0008] Based on the meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed, the CO assimilation grid flux data set and CO 2Assimilation of grid flux data sets, CO prediction regional fluxes and CO 2 Predict regional fluxes;

[0009] Based on the predicted regional flux of CO and the CO 2 Predict regional fluxes to obtain CO and CO 2 The regional emission scaling factor is based on the CO assimilation grid flux data set and the CO 2 Assimilate the grid flux data set to obtain CO and CO for each spatial grid 2 Grid emission scale factor;

[0010] The gas data includes CO gas data and CO 2 The CO gas data includes CO initial boundary field data, preset mixed gas initial boundary field data, CO ecological flux data, CO wildfire flux data, CO anthropogenic flux data and CO satellite observation data. 2 Gas data including CO 2 Initial boundary field data, CO 2 Flux data and CO 2 Satellite observation data.

[0011] Preferably, the preset acquisition method is:

[0012] The meteorological reanalysis data at the time to be analyzed is input into a preset atmospheric chemistry model to obtain meteorological initial boundary field data, and Gaussian perturbation is performed on the meteorological initial boundary field data to obtain a preset number of perturbed meteorological initial boundary field data sets;

[0013] Adding the preset gas data to all the disturbance meteorological initial boundary field data sets respectively to form a preset number of disturbance initial boundary field data sets;

[0014] Interpolating the flux data of the Class A gas data in the gas data of the area to be analyzed at the time to be analyzed into the spatial grid of the preset atmospheric chemistry model to generate a grid flux data set, and performing Gaussian perturbation on the grid flux data to obtain a perturbed grid flux data set;

[0015] The satellite observation data of the type A gas data in the gas data of the area to be analyzed at the time to be analyzed are processed in a localized manner to obtain the target observation data;

[0016] Based on the target observation data, the initial field data in all the perturbed initial boundary field data sets and the perturbed grid flux data sets are assimilated using a set adaptive Kalman filter method to obtain a preset number of assimilated initial field data sets and assimilated grid flux data sets of gas A;

[0017] Based on all the assimilated initial field data sets, the boundary field data in the corresponding perturbed initial boundary field data sets are updated respectively to obtain a preset number of updated boundary field data sets, and all the assimilated initial field data sets and all the updated boundary field data sets correspondingly form a preset number of assimilated initial boundary field data sets;

[0018] Inputting all the assimilated initial boundary field data sets into the preset atmospheric chemistry model in sequence to obtain a preset number of predicted gas initial boundary field data sets at the next moment of the time to be analyzed in the area to be analyzed;

[0019] Obtaining a predicted regional flux of gas A in the region to be analyzed at the time to be analyzed based on the area of ​​the region to be analyzed and the assimilated grid flux data set of gas A;

[0020] Wherein, the preset gas data is:

[0021] If there is currently a set of predicted gas initial boundary field data of a preset number of gas A in the area to be analyzed at the time to be analyzed, Gaussian perturbation is performed on the preset mixed gas initial boundary field data in the A-type gas data in the area to be analyzed at the time to be analyzed to obtain a preset number of perturbed preset mixed gas initial boundary field data sets, and the set of predicted gas initial boundary field data of the preset number of gas A in the area to be analyzed at the time to be analyzed and the preset number of perturbed preset mixed gas initial boundary field data are combined as the preset gas data; otherwise, Gaussian perturbation is performed on the initial boundary field data of gas A in the A-type gas data in the area to be analyzed at the time to be analyzed and the preset mixed gas initial boundary field data to obtain a preset number of perturbed gas initial boundary field data sets and a preset number of perturbed preset mixed gas initial boundary field data sets, and the perturbed gas initial boundary field data set and the perturbed preset mixed gas initial boundary field data set are combined as the preset gas data; A is CO or CO 2 .

[0022] Preferably, before the step of determining the area to be analyzed and the time to be analyzed, the step further includes:

[0023] Determine the time resolution and spatial resolution, the time to be analyzed is different from the time before the time to be analyzed and the time after the time to be analyzed by a time resolution; use the preset mixed gas initial boundary field data, meteorological reanalysis data, CO ecological flux data, CO wildfire flux data, and CO anthropogenic flux data as state quantities in the CO assimilation process, and use the CO 2 Initial boundary field data, CO 2 Flux data and meteorological reanalysis data as CO 2 The state quantity in the assimilation process;

[0024] Determine the atmospheric physical parameters and chemical parameters of the preset atmospheric chemistry model.

[0025] Preferably, the preset mixed gas initial boundary field data includes gas initial boundary field data of all gases that can be processed by the preset atmospheric chemistry model and are currently accessible and affect CO concentration.

[0026] Preferably, the CO 2 Flux data for CO 2 Anthropogenic flux data, CO 2 Ecological flux data, CO 2 The sum of ocean flux data and CO2 wildfire flux data.

[0027] Preferably, the preset number is greater than 20.

[0028] Preferably, the updating formula for updating the boundary field data in the corresponding disturbance initial boundary field data set based on the assimilated initial field data set is:

[0029] TEND new =BDY old +F(BDY old -INP mean )

[0030] Among them, TEND new Indicates the new boundary condition value, BDY old Indicates the old boundary condition value, INP mean represents the initial field data, and F represents the distance weight function.

[0031] In order to solve the above technical problems, the present invention also provides a CO and CO 2 An emission proportionality coefficient estimation device includes a to-be-analyzed data determination unit, a data acquisition unit, a predicted area flux acquisition unit, and a proportionality coefficient acquisition unit;

[0032] The to-be-analyzed data determination unit is used to determine the to-be-analyzed area and the to-be-analyzed time;

[0033] The data acquisition unit is used to acquire meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed;

[0034] The prediction area flux acquisition unit is used to acquire the CO assimilation grid flux data set and CO at the time to be analyzed through a preset acquisition method based on the meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed. 2 Assimilation of grid flux data sets, CO prediction regional fluxes and CO 2 Predict regional fluxes;

[0035] The proportional coefficient acquisition unit is used to predict the regional flux of CO and the CO 2 Predict regional fluxes to obtain CO and CO 2 The regional emission scaling factor is based on the CO assimilation grid flux data set and the CO 2 Assimilate the grid flux data set to obtain CO and CO for each spatial grid 2 Grid emission scale factor;

[0036] The gas data includes CO gas data and CO 2 The CO gas data includes CO initial boundary field data, preset mixed gas initial boundary field data, CO ecological flux data, CO wildfire flux data, CO anthropogenic flux data and CO satellite observation data. 2 Gas data include CO2 initial boundary field data, CO 2 Flux data and CO 2 Satellite observation data.

[0037] In order to solve the above technical problems, the present invention also provides a storage medium on which a computer program is stored, and when the program is executed by a processor, CO and CO are realized. 2 Emission proportionality factor estimation method.

[0038] In order to solve the above technical problem, the present invention further provides a terminal, comprising: a processor and a memory, wherein the memory is communicatively connected to the processor;

[0039] The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory so that the terminal executes the CO and CO 2 Emission proportionality factor estimation method.

[0040] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:

[0041] Applying the CO and CO provided by the embodiment of the present invention 2 The emission ratio coefficient estimation method is to convert CO and CO 2 The initial boundary field data are combined with the meteorological reanalysis data at the relative time, and satellite observation data are introduced to realize data assimilation to obtain CO and CO at the relative time. 2 Assimilated flux data, and then the assimilated CO flux data and assimilated CO 2 The flux data is compared to obtain CO and CO 2 Emission proportional coefficient; In order to improve the accuracy, while obtaining the flux data, the atmospheric chemistry model is also used to obtain the CO prediction gas initial boundary field data and CO2 Predict the gas initial boundary field data as the basis for obtaining the flux data at the next moment. By setting the area to be analyzed and the time to be analyzed, the method of the present invention can obtain CO2 data for different countries, provinces, cities and regions around the world. 2 The proportional coefficient with spatiotemporal characteristics of CO; and the proportional coefficients obtained in different regions are comparable.

[0042] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0044] Figure 1 The embodiment of the present invention shows CO and CO 2 Schematic diagram of the emission proportionality factor estimation method flow chart;

[0045] Figure 2 The second embodiment of the present invention shows CO and CO 2 Schematic diagram of the emission ratio coefficient estimation device structure;

[0046] Figure 3 A schematic diagram of the structure of a terminal according to a fourth embodiment of the present invention is shown. DETAILED DESCRIPTION

[0047] The following will describe the implementation methods of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0048] Existing observation data from ground stations are used to conduct CO 2 The main data source for the estimation of the CO ratio coefficient is ground stations, and satellite data is not used. 2 The CO ratio coefficient uses concentration data, and its artificial CO 2 The CO2 ratio coefficient is directly derived from inventory data without model optimization. The above factors make the existing CO 2 The estimation of the CO proportionality coefficient is not continuous in time and space, and the accuracy is not high.

[0049] Embodiment 1

[0050] In order to solve the technical problems existing in the prior art, the embodiment of the present invention provides a CO and CO 2 Emission proportionality factor estimation method.

[0051] Figure 1 The embodiment of the present invention shows CO and CO 2 Schematic diagram of the emission ratio coefficient estimation method flow chart; reference Figure 1 As shown, in the embodiment of the present invention, CO and CO 2 The emission proportionality coefficient estimation method includes the following steps.

[0052] Step S101, determining the area to be analyzed, the time to be analyzed, the spatial resolution and the temporal resolution.

[0053] To facilitate the design, we set the area to be analyzed and the time to be analyzed synchronously with the spatial resolution and time resolution. Specifically, the area to be studied is set as the area to be analyzed, and the maximum longitude and latitude and minimum longitude and latitude of the area to be analyzed are determined as the location basis for obtaining meteorological reanalysis data and meteorological data. The time to be studied is set as the time to be analyzed, and the time to be analyzed can include multiple target moments, each of which is the time at which CO and CO 2 The moment of the emission proportional coefficient, using the method of the embodiment of the present invention, multiple target moments can be analyzed in sequence as the moments to be analyzed. A spatial resolution close to the satellite spatial resolution is selected as the spatial resolution; preferably, the spatial resolution can be selected to be close to the satellite spatial resolution. At the same time, the time resolution is selected according to the needs. For example, if the daily changes are studied, 1 hour can be selected as the time resolution, and if the seasonal changes are studied, 6 hours or days can be selected as the time resolution. When setting the target moment, the multiple target moments are separated by one time resolution in sequence.

[0054] Step S102: Determine the CO assimilation state quantity composition and CO 2 Assimilation state quantity composition.

[0055] Specifically, the preset mixed gas initial boundary field data, meteorological reanalysis data, CO ecological flux data, CO wildfire flux data, and CO anthropogenic flux data are used as state quantities in the CO assimilation process. 2 Initial boundary field data, CO 2 Flux data and meteorological reanalysis data as CO 2 Assimilation system state quantity as CO 2 It should be noted that the CO assimilation state quantity is composed of CO 2 The assimilation state quantity can be modified according to the actual situation, and there is no fixed restriction on it.

[0056] Step S103, determining the atmospheric physical parameters and chemical parameters of the preset atmospheric chemical model.

[0057] Preferably, the atmospheric physical parameters of the preset atmospheric chemical model can be set as: mp_physis=17; and the chemical model parameters can be selected as: chem_opt=112 or 14 for CO assimilation, and chem_opt=16 for CO2 assimilation. It should also be noted that the atmospheric physical parameters and chemical parameters can be modified according to actual conditions, and no fixed restrictions are imposed on them.

[0058] Step S104, obtaining meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed.

[0059] Specifically, it is necessary to obtain meteorological data and gas data for the time to be analyzed in the area to be analyzed. Meteorological data include: meteorological reanalysis data for the time to be analyzed in the area to be analyzed can be downloaded from the NCAR website or other WMO GRIB2 format meteorological data provider websites, such as ds083.2. Gas data include: downloading CO initial boundary field data (such as ds313.7) and preset mixed gas initial boundary field data from the NCAR website; downloading CO2 initial boundary field data (such as CT2019B_CO2_glb) from the CarbonTracker website; downloading CO ecological flux data (such as MAGANv2.1), CO wildfire flux data (such as FiNNv1.5) and CO anthropogenic flux data (such as EDGARv4.3.2) from the UCAR website; downloading CO2 flux data (such as CT2019_flux) from the CarbonTracker website; downloading CO satellite observation data (such as MOPITT V8) and CO from the NCAR website. 2 Satellite observation data (such as OCO-2V10). It should be noted that the above data can also be downloaded from other suitable websites and are not fixed here.

[0060] The above gas data can be divided into CO type gas data and CO 2 Gas data, including CO initial boundary field data, preset mixed gas initial boundary field data, CO ecological flux data, CO wildfire flux data, CO anthropogenic flux data and CO satellite observation data, CO 2 Gas data including CO 2 Initial boundary field data, CO 2 Flux data and CO 2Satellite observation data. The preset mixed gas initial boundary field data includes the gas initial boundary field data of all gases that can be processed by the preset atmospheric chemistry model and can be obtained at present and affect the CO concentration. Since the gas initial boundary field data that can be processed by the preset atmospheric chemistry model and affect the CO concentration are limited, and not all gas initial boundary field data that affect the CO concentration can be downloaded, we select the intersection of the gas initial boundary field data that can be processed by the preset atmospheric chemistry model and the gas initial boundary field data that can be obtained and affect the CO concentration as the preset mixed gas initial boundary field data. Table 1 shows an example of a partial list of gases that affect the CO concentration.

[0061] Table 1 Example of a list of gases that affect CO concentration

[0062]

[0063] Step S105, based on the meteorological reanalysis data and gas data of the analyzed area at the analyzed time, obtain the CO assimilation grid flux data set and CO 2 Assimilation of grid flux data sets, CO prediction regional fluxes and CO 2 Predict regional fluxes.

[0064] Specifically, it is necessary to obtain the CO assimilation grid flux data set and CO 2 Assimilation of grid flux data sets, CO prediction regional fluxes and CO 2 Predict regional flux. The CO is obtained by the preset acquisition method. 2 Assimilation of gridded flux data sets and CO2 prediction regional fluxes and obtaining CO2 prediction regional fluxes and CO2 2 The process of predicting regional fluxes is the same, so for simplicity, we use A to represent CO or CO in the default acquisition method. 2 The specific preset acquisition method includes the following steps.

[0065] Step S501, input the meteorological reanalysis data at the time to be analyzed into a preset atmospheric chemistry model to obtain meteorological initial boundary field data, and perform Gaussian perturbation on the meteorological initial boundary field data to obtain a preset number of perturbed meteorological initial boundary field data sets.

[0066] Specifically, since this embodiment needs to be applied to the atmospheric chemistry model, the atmospheric chemistry model needs to be set based on the parameters set in step S101 and step S103, and the set atmospheric chemistry model is used as the preset atmospheric chemistry model. Then, the meteorological reanalysis data of the area to be analyzed at the time to be analyzed is input into the preset atmospheric chemistry model to obtain meteorological initial boundary field data, which includes meteorological initial field data and meteorological boundary field data.

[0067] The process of obtaining the meteorological initial boundary field data based on the preset atmospheric chemistry model is essentially as follows: the spatial grid information is generated by the geogrid program in the preset atmospheric chemistry model. It should be noted that the spatial grid information is generated based on the static geographic data of the preset area, and the static geographic data is downloaded from the WPS_GEOG website; then the ungrib program in the preset atmospheric chemistry model extracts meteorological data matching the spatial grid information from the meteorological reanalysis data, and then the metgrid program in the preset atmospheric chemistry model interpolates the meteorological data into the grid, and finally the real program in the preset atmospheric chemistry model generates the meteorological initial boundary field data.

[0068] After obtaining the meteorological initial boundary field data, a Gaussian perturbation with a mean of 0 is added to the meteorological initial boundary field data through 3DVAR (three-dimensional variation), and in order to improve data accuracy, we set a preset number of disturbed meteorological initial boundary field data sets to be generated through Gaussian perturbation, and preferably, the preset number is 20. Step S502, respectively add the preset gas data to all disturbed meteorological initial boundary field data sets to form a preset number of disturbed initial boundary field data sets.

[0069] Specifically, the selected preset gas data is different according to different situations. Further, if there is currently a set of predicted gas initial boundary field data of a preset number of A gases in the area to be analyzed at the time to be analyzed, that is, a set of predicted gas initial boundary field data of a preset number of A gases at the time to be analyzed obtained when the moment before the time to be analyzed in the area to be analyzed is the time to be analyzed, then Gaussian perturbation is performed on the preset mixed gas initial boundary field data in the A-type gas data in the area to be analyzed at the time to be analyzed to obtain a preset number of perturbed preset mixed gas initial boundary field data sets, and the set of predicted gas initial boundary field data of the preset number of A gases in the area to be analyzed at the time to be analyzed and the preset number of perturbed preset mixed gas initial boundary field data are combined as the preset gas data.

[0070] If there is no predicted gas initial boundary field data set of the preset number of A gases at the time to be analyzed, that is, the previous target time of the time to be analyzed is not used as the time to be analyzed to obtain the proportional coefficient, then it is necessary to perform Gaussian perturbations on the initial boundary field data of A gas and the preset mixed gas initial boundary field data in the A-type gas data at the time to be analyzed to obtain the preset number of disturbed gas initial boundary field data sets and the preset number of disturbed preset mixed gas initial boundary field data sets, and combine the preset number of disturbed gas initial boundary field data and the preset number of disturbed preset mixed gas initial boundary field data as the preset gas data. The Gaussian perturbations in this step are all disturbances with a mean of 0.

[0071] It should be noted that when A is CO 2 When CO 2 The gas-like data does not contain the preset mixed gas initial boundary field data, and in this case, the preset mixed gas initial boundary field data can be treated as no data.

[0072] After the preset gas data are selected, they are added to the disturbance meteorological initial boundary field data set to form a preset number of disturbance initial boundary field data sets.

[0073] Step S503, interpolate the flux data of Class A gas data in the gas data of the area to be analyzed at the time to be analyzed into the spatial grid of the preset atmospheric chemistry model to generate grid flux data, and perform Gaussian perturbation on the grid flux data to obtain a perturbed grid flux data set.

[0074] Specifically, this step requires that the flux data in the Class A gas data in the gas data of the area to be analyzed at the time to be analyzed be interpolated into the spatial grid of the preset atmospheric chemistry model to generate grid flux data, and then the grid flux data is Gaussian perturbed to obtain a set of perturbed grid flux data.

[0075] Furthermore, when downloading flux data from the UCAR website, the bio_emis tool, fire_emis tool, and anthro_emis tool are also downloaded. At this time, when A is CO, the anthro_emis tool is used to interpolate the CO artificial flux data into the spatial grid of the preset atmospheric chemistry model to generate CO artificial grid flux data; and the bio_emis tool is used to interpolate the CO ecological flux data into the spatial grid of the preset atmospheric chemistry model to generate CO ecological grid flux data; finally, the fire_emis tool is used to interpolate the CO combustion flux data into the spatial grid of the preset atmospheric chemistry model to generate CO combustion grid flux data. Then, Gaussian perturbations with a mean of 0 are performed on the CO2 anthropogenic grid flux data, CO2 ecological grid flux data, and CO2 combustion grid flux data, respectively, to generate the CO2 perturbed anthropogenic grid flux data set, CO2 perturbation ecological grid flux data set, and CO2 perturbation combustion grid flux data set, respectively. The CO2 perturbation anthropogenic grid flux data set, the CO2 perturbation ecological grid flux data set, and the CO2 perturbation combustion grid flux data set together constitute the CO2 perturbation grid flux data set.

[0076] When A is CO 2 When CO 2 The flux data are interpolated into the spatial grid of the preset atmospheric chemistry model to generate CO 2 Grid flux data and CO 2 The grid flux data is perturbed with a mean of 0 to generate CO 2 Perturbation grid flux data set. And it should be noted that CO 2 Flux data for CO 2 Anthropogenic flux data, CO 2 Ecological flux data, CO 2 Ocean flux data and CO 2 Aggregation of wildfire flux data.

[0077] Step S504, the satellite observation data in the Class A gas data in the gas data of the area to be analyzed at the time to be analyzed is processed in a localized manner to obtain target observation data.

[0078] Specifically, this step needs to obtain the target observation data based on the satellite observation data in the A-type gas data in the gas data to be analyzed. Furthermore, when A is CO, the CO satellite observation data is processed using a localized method to obtain the CO target observation data, where the straight-line distance between observations is required to be less than 0.1 radians. It should be noted that the straight-line distance requirement between observations can also be set to other values, and there is no fixed restriction on it here. When A is CO 2 When CO 2Satellite observation data are processed using a localized method to obtain CO 2 Target observation data, where the observation mean is 10s, and the method for calculating the mean uses the probability expectation method. It should be noted that the observation mean can also be set to other values, and there is no fixed restriction on it here.

[0079] Step S505, based on the target observation data, the set adaptive Kalman filter method is used to assimilate the initial field data and the disturbance grid flux data set in all the disturbance initial boundary field data sets to obtain a preset number of assimilated initial field data sets and assimilated grid flux data sets of gas A.

[0080] Specifically, based on the target observation data obtained in step S504, the set adaptive Kalman filter method is used to assimilate the initial field data in all the perturbed initial boundary field data sets and the perturbed grid flux data sets, respectively, to obtain a preset number of assimilated initial field data sets and an assimilated grid flux data set of gas A. For example, based on the CO target observation data, the set adaptive Kalman filter method is used to assimilate the initial field data in all the CO perturbation initial boundary field data sets and the CO perturbation grid flux data sets, respectively, to obtain a preset number of CO assimilated initial field data sets and a CO assimilated grid flux data set; similarly, a preset number of CO assimilated initial field data sets and a CO assimilated grid flux data set are obtained. 2 Assimilation of initial field data set and CO 2 Assimilate gridded flux data sets.

[0081] Step S506, based on all assimilated initial field data sets, the boundary field data in the corresponding perturbation initial boundary field data sets are updated respectively to obtain a preset number of updated boundary field data sets, and all assimilated initial field data sets and all updated boundary field data sets are correspondingly formed into a preset number of assimilated initial boundary field data sets.

[0082] Specifically, the assimilation formula for assimilating the boundary field data in the corresponding perturbed initial boundary field data set based on the assimilated initial field data set is:

[0083] TEND new =BDY old +F(BDY old -INP mean )

[0084] Among them, TEND new Indicates the new boundary condition value, BDY old Indicates the old boundary condition value, INP mean represents the initial field data, and F represents the distance weight function.

[0085] Step S507, all assimilated initial boundary field data sets are sequentially input into a preset atmospheric chemistry model to obtain a preset number of predicted gas initial boundary field data sets at the next moment of the time to be analyzed in the area to be analyzed.

[0086] Specifically, all assimilated initial boundary field data sets are sequentially input into the preset atmospheric chemistry model, and a preset number of predicted gas initial boundary field data sets of the next moment of the time to be analyzed in the area to be analyzed can be obtained. Similarly, the preset number of predicted gas initial boundary field data sets of gas A at the time to be analyzed in step S502 are the CO and CO at the moment before the time to be analyzed. 2 Similarly, the predicted gas initial boundary field data set of the preset number of A gases at the next moment to be analyzed obtained in this step can also be applied to CO and CO at the next moment to be analyzed. 2 In the step of obtaining the emission ratio coefficient.

[0087] Step S508, based on the area of ​​the to-be-analyzed region and the assimilated grid flux data set of gas A, the predicted regional flux of gas A in the to-be-analyzed region at the to-be-analyzed time is obtained.

[0088] Specifically, the area of ​​the area to be analyzed is introduced. Based on the assimilated grid flux data set of gas A, the method of first calculating the average flux per unit area and then calculating the total flux through the regional area is adopted to obtain the predicted regional flux of gas A in the area to be analyzed at the time to be analyzed.

[0089] A is used as CO and CO 2 , repeat the above steps S501-S508 to obtain the CO predicted regional flux and the CO2 predicted regional flux.

[0090] Step S106: predicting regional flux and CO based on CO 2 Predict regional fluxes to obtain CO and CO 2 The regional emission scaling factor is based on the CO assimilation grid flux data set and CO 2 Assimilate the grid flux data set to obtain CO and CO for each spatial grid 2 Grid emission scale factor.

[0091] Specifically, due to the acquisition of CO assimilation grid flux data sets and CO 2 The same static geographic data is used when assimilating the grid flux data set, so the CO assimilation grid flux data set and CO 2 The assimilated grid flux data sets have the same spatial grid information, so there is no need to align them. 2The grid flux data set is assimilated to obtain the CO and CO2 grid emission ratio coefficients for each spatial grid. Then, the regional flux and CO are predicted based on CO 2 Predict regional fluxes to obtain CO and CO 2 Regional emission scaling factor.

[0092] It should be noted that when the time to be analyzed includes multiple target moments, each target moment can be used as the time to be analyzed according to the time sequence, and the CO and CO of all target moments in the time to be analyzed in the area to be analyzed can be obtained by repeating the above steps S101-S106. 2 Emission proportionality factor.

[0093] CO and CO provided in the embodiment of the present invention 2 The emission ratio coefficient estimation method is to convert CO and CO 2 The initial boundary field data are combined with the meteorological reanalysis data at the relative time, and satellite observation data are introduced to realize data assimilation to obtain CO and CO at the relative time. 2 Then, the assimilated CO flux data and the assimilated CO2 flux data of the same grid are compared to obtain the CO and CO 2 Emission proportional coefficient; In order to improve the accuracy, while obtaining the flux data, the atmospheric chemistry model is also used to obtain the CO prediction gas initial boundary field data and CO 2 Predict the gas initial boundary field data as the basis for obtaining the flux data at the next moment. By setting the area to be analyzed and the time to be analyzed, the method of the present invention can obtain CO2 data for different countries, provinces, cities and regions around the world. 2 The proportional coefficient with spatiotemporal characteristics of CO; and the proportional coefficients obtained in different regions are comparable.

[0094] Embodiment 2

[0095] In order to solve the above technical problems existing in the prior art, the embodiment of the present invention also provides a CO and CO 2 Emission proportionality factor estimation device.

[0096] Figure 2 The second embodiment of the present invention shows CO and CO 2 Schematic diagram of the emission ratio coefficient estimation device; reference Figure 2 As shown, in the embodiment of the present invention, CO and CO 2 The emission proportionality coefficient estimation device includes a data determination unit to be analyzed, a data acquisition unit, a predicted area flux acquisition unit and a proportionality coefficient acquisition unit.

[0097] The to-be-analyzed data determining unit is used to determine the to-be-analyzed area and the to-be-analyzed time.

[0098] The data acquisition unit is used to acquire the meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed.

[0099] The prediction area flux acquisition unit is used to obtain the CO assimilation grid flux data set and CO at the time to be analyzed through a preset acquisition method based on the meteorological reanalysis data and gas data at the time to be analyzed in the area to be analyzed. 2 Assimilation of grid flux data sets, CO prediction regional fluxes and CO 2 Predict regional fluxes.

[0100] The proportional coefficient acquisition unit is used to predict the regional flux based on the CO and the CO 2 Predict regional fluxes to obtain CO and CO 2 The regional emission scaling factor is based on the CO assimilation grid flux data set and the CO 2 Assimilate the grid flux data set to obtain CO and CO for each spatial grid 2 Grid emission scale factor.

[0101] Among them, gas data includes CO gas data and CO 2 Gas data of CO, including CO initial boundary field data, preset mixed gas initial boundary field data, CO ecological flux data, CO wildfire flux data, CO anthropogenic flux data and CO satellite observation data, the CO 2 Gas data including CO 2 Initial boundary field data, CO 2 Flux data and CO 2 Satellite observation data.

[0102] CO and CO provided in the embodiment of the present invention 2 Emission ratio coefficient estimation device, CO and CO 2 The initial boundary field data are combined with the meteorological reanalysis data at the relative time, and satellite observation data are introduced to realize data assimilation to obtain CO and CO at the relative time. 2 Assimilated flux data, and then the assimilated CO flux data and assimilated CO 2 The flux data is compared to obtain CO and CO 2 Emission proportional coefficient; In order to improve the accuracy, while obtaining the flux data, the atmospheric chemistry model is also used to obtain the CO prediction gas initial boundary field data and CO 2 Predict the gas initial boundary field data as the basis for obtaining the flux data at the next moment. By setting the area to be analyzed and the time to be analyzed, the device of the present invention can obtain CO2 data from different countries, provinces, cities and regions around the world. 2The proportional coefficient with spatiotemporal characteristics of CO; and the proportional coefficients obtained in different regions are comparable.

[0103] Embodiment 3

[0104] In order to solve the above technical problems existing in the prior art, an embodiment of the present invention further provides a storage medium storing a computer program, which can realize the CO and CO in the first embodiment when the computer program is executed by the processor. 2 All steps in the emission scaling factor estimation method.

[0105] CO and CO 2 The specific steps of the emission ratio coefficient estimation method and the beneficial effects obtained by applying the readable storage medium provided in the embodiment of the present invention are the same as those in the first embodiment, and will not be described in detail here.

[0106] It should be noted that the storage medium includes various media that can store program codes, such as ROM, RAM, magnetic disk or optical disk.

[0107] Embodiment 4

[0108] In order to solve the above technical problems existing in the prior art, an embodiment of the present invention further provides a terminal.

[0109] Figure 3 The schematic diagram of the structure of the fourth terminal of the embodiment of the present invention is shown. Figure 3 The terminal of this embodiment includes a processor and a memory connected to each other; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal can implement the embodiment 1 CO and CO when executing 2 All steps in the emission scaling factor estimation method.

[0110] CO and CO 2 The specific steps of the emission ratio coefficient estimation method and the beneficial effects obtained by applying the terminal provided by the embodiment of the present invention are the same as those in the first embodiment, and will not be described in detail here.

[0111] It should be noted that the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage. Similarly, the processor may also be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0112] Although the embodiments disclosed in the present invention are as above, the contents described are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A method for estimating the ratio coefficient of CO and CO2 emissions, comprising: Determine the area and time to be analyzed; Obtain meteorological reanalysis data and gas data for the area to be analyzed at the time to be analyzed; Based on the meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed, a CO assimilation grid flux data set, a CO2 assimilation grid flux data set, a CO prediction regional flux, and a CO2 prediction regional flux at the time to be analyzed are obtained through a preset acquisition method; Obtaining a CO to CO2 regional emission ratio coefficient based on the CO predicted regional flux and the CO2 predicted regional flux, and obtaining a CO to CO2 grid emission ratio coefficient of each spatial grid based on the CO assimilation grid flux data set and the CO2 assimilation grid flux data set; The gas data include CO gas data and CO2 gas data, the CO gas data include CO initial boundary field data, preset mixed gas initial boundary field data, CO ecological flux data, CO wildfire flux data, CO anthropogenic flux data and CO satellite observation data, and the CO2 gas data include CO2 initial boundary field data, CO2 flux data and CO2 satellite observation data; The preset acquisition method is: The meteorological reanalysis data at the time to be analyzed is input into a preset atmospheric chemistry model to obtain meteorological initial boundary field data, and Gaussian perturbation is performed on the meteorological initial boundary field data to obtain a preset number of perturbed meteorological initial boundary field data sets; Adding the preset gas data to all the disturbance meteorological initial boundary field data sets respectively to form a preset number of disturbance initial boundary field data sets; Interpolating the flux data of the Class A gas data in the gas data of the area to be analyzed at the time to be analyzed into the spatial grid of the preset atmospheric chemistry model to generate a grid flux data set, and performing Gaussian perturbation on the grid flux data to obtain a perturbed grid flux data set; The satellite observation data of the type A gas data in the gas data of the area to be analyzed at the time to be analyzed are processed in a localized manner to obtain the target observation data; Based on the target observation data, the initial field data in all the perturbed initial boundary field data sets and the perturbed grid flux data sets are assimilated using a set adaptive Kalman filter method to obtain a preset number of assimilated initial field data sets and assimilated grid flux data sets of gas A; Based on all the assimilated initial field data sets, the boundary field data in the corresponding perturbed initial boundary field data sets are updated respectively to obtain a preset number of updated boundary field data sets, and all the assimilated initial field data sets and all the updated boundary field data sets correspondingly form a preset number of assimilated initial boundary field data sets; Inputting all the assimilated initial boundary field data sets into the preset atmospheric chemistry model in sequence to obtain a preset number of predicted gas initial boundary field data sets at the next moment of the time to be analyzed in the area to be analyzed; Obtaining a predicted regional flux of gas A in the region to be analyzed at the time to be analyzed based on the area of ​​the region to be analyzed and the assimilated grid flux data set of gas A; Wherein, the preset gas data is: If there is currently a predicted gas initial boundary field data set of a preset number of A gases in the area to be analyzed at the time to be analyzed, Gaussian perturbation is performed on the preset mixed gas initial boundary field data in the A-type gas data in the area to be analyzed at the time to be analyzed to obtain a preset number of perturbed preset mixed gas initial boundary field data sets, and the predicted gas initial boundary field data set of the preset number of A gases in the area to be analyzed at the time to be analyzed and the preset number of perturbed preset mixed gas initial boundary field data are combined as the preset gas data; otherwise, Gaussian perturbation is performed on the initial boundary field data of A gas in the A-type gas data in the area to be analyzed at the time to be analyzed and the preset mixed gas initial boundary field data to obtain a preset number of perturbed gas initial boundary field data sets and a preset number of perturbed preset mixed gas initial boundary field data sets, and the perturbed gas initial boundary field data set and the perturbed preset mixed gas initial boundary field data are combined as the preset gas data; A is CO or CO2.

2. The estimation method according to claim 1, characterized in that: Before determining the area to be analyzed and the time to be analyzed, the following steps are also included: Determine the time resolution and spatial resolution, the time to be analyzed is different from the time before the time to be analyzed and the time after the time to be analyzed by a time resolution; use the preset mixed gas initial boundary field data, meteorological reanalysis data, CO ecological flux data, CO wildfire flux data, and CO anthropogenic flux data as state quantities in the CO assimilation process, and use the CO2 initial boundary field data, CO2 flux data, and meteorological reanalysis data as state quantities in the CO2 assimilation process; Determine the atmospheric physical parameters and chemical parameters of the preset atmospheric chemistry model.

3. The estimation method according to claim 2, characterized in that: The preset mixed gas initial boundary field data includes gas initial boundary field data of all gases that can be processed by the preset atmospheric chemistry model and are currently available and affect CO concentration.

4. The estimation method according to claim 1, characterized in that: The CO2 flux data is the sum of CO2 anthropogenic flux data, CO2 ecological flux data, CO2 ocean flux data and CO2 wildfire flux data.

5. The estimation method according to claim 1, characterized in that: The preset number is greater than 20.

6. The estimation method according to claim 1, characterized in that: The updating formula for updating the boundary field data in the corresponding disturbance initial boundary field data set based on the assimilated initial field data set is: TEND new =BDY old +F(BDY old -INP mean ) Among them, TEND new Indicates the new boundary condition value, BDY old Indicates the old boundary condition value, INP mean represents the initial field data, and F represents the distance weight function.

7. A device for estimating the ratio coefficient of CO and CO2 emissions, comprising a unit for determining data to be analyzed, a data acquisition unit, a prediction area flux acquisition unit and a ratio coefficient acquisition unit; The to-be-analyzed data determination unit is used to determine the to-be-analyzed area and the to-be-analyzed time; The data acquisition unit is used to acquire meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed; The predicted regional flux acquisition unit is used to acquire the CO assimilation grid flux data set, the CO2 assimilation grid flux data set, the CO predicted regional flux and the CO2 predicted regional flux at the time to be analyzed through a preset acquisition method based on the meteorological reanalysis data and gas data of the area to be analyzed at the time to be analyzed; The proportional coefficient acquisition unit is used to acquire the CO and CO2 regional emission proportional coefficient based on the CO predicted regional flux and the CO2 predicted regional flux, and acquire the CO and CO2 grid emission proportional coefficient of each spatial grid based on the CO assimilation grid flux data set and the CO2 assimilation grid flux data set; in, The gas data includes CO gas data and CO2 gas data, wherein the CO gas data includes CO initial boundary field data, preset mixed gas initial boundary field data, CO ecological flux data, CO wildfire flux data, CO anthropogenic flux data and CO satellite observation data, and the CO2 gas data includes CO2 initial boundary field data, CO2 flux data and CO2 satellite observation data; The preset acquisition method is: The meteorological reanalysis data at the time to be analyzed is input into a preset atmospheric chemistry model to obtain meteorological initial boundary field data, and Gaussian perturbation is performed on the meteorological initial boundary field data to obtain a preset number of perturbed meteorological initial boundary field data sets; Adding the preset gas data to all the disturbance meteorological initial boundary field data sets respectively to form a preset number of disturbance initial boundary field data sets; Interpolating the flux data of the Class A gas data in the gas data of the area to be analyzed at the time to be analyzed into the spatial grid of the preset atmospheric chemistry model to generate a grid flux data set, and performing Gaussian perturbation on the grid flux data to obtain a perturbed grid flux data set; The satellite observation data of the type A gas data in the gas data of the area to be analyzed at the time to be analyzed are processed in a localized manner to obtain the target observation data; Based on the target observation data, the initial field data in all the perturbed initial boundary field data sets and the perturbed grid flux data sets are assimilated using a set adaptive Kalman filter method to obtain a preset number of assimilated initial field data sets and assimilated grid flux data sets of gas A; Based on all the assimilated initial field data sets, the boundary field data in the corresponding perturbed initial boundary field data sets are updated respectively to obtain a preset number of updated boundary field data sets, and all the assimilated initial field data sets and all the updated boundary field data sets correspondingly form a preset number of assimilated initial boundary field data sets; Inputting all the assimilated initial boundary field data sets into the preset atmospheric chemistry model in sequence to obtain a preset number of predicted gas initial boundary field data sets at the next moment of the time to be analyzed in the area to be analyzed; Obtaining a predicted regional flux of gas A in the region to be analyzed at the time to be analyzed based on the area of ​​the region to be analyzed and the assimilated grid flux data set of gas A; Wherein, the preset gas data is: If there is currently a predicted gas initial boundary field data set of a preset number of A gases in the area to be analyzed at the time to be analyzed, Gaussian perturbation is performed on the preset mixed gas initial boundary field data in the A-type gas data in the area to be analyzed at the time to be analyzed to obtain a preset number of perturbed preset mixed gas initial boundary field data sets, and the predicted gas initial boundary field data set of the preset number of A gases in the area to be analyzed at the time to be analyzed and the preset number of perturbed preset mixed gas initial boundary field data are combined as the preset gas data; otherwise, Gaussian perturbation is performed on the initial boundary field data of A gas in the A-type gas data in the area to be analyzed at the time to be analyzed and the preset mixed gas initial boundary field data to obtain a preset number of perturbed gas initial boundary field data sets and a preset number of perturbed preset mixed gas initial boundary field data sets, and the perturbed gas initial boundary field data set and the perturbed preset mixed gas initial boundary field data are combined as the preset gas data; A is CO or CO2.

8. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements the method for estimating the CO and CO2 emission ratio coefficient according to any one of claims 1 to 6.

9. A terminal, characterized in that: include: A processor and a memory, wherein the memory is communicatively connected to the processor; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes the method for estimating the CO and CO2 emission ratio coefficient according to any one of claims 1 to 6.

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